adding graph timeseries#807
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dario-coscia
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dario-coscia
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Minor comment on an extra feature, but overall looks great. Be aware that tests are failing
| residuals = [] | ||
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| # Iterate over the time steps | ||
| for step in range(1, batch["input"].shape[2]): |
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@GiovanniCanali what do you think to add the pushforward trick here as well? Is it a condition thing or solver thing? Having it is very easy (we just need the no grad option)
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This is definitely a condition-level concern, since gradient computation must be enabled or disabled when evaluating the residual between the model prediction and the target. As you noted, the implementation should be straightforward. Since the forward method is inherited from TimeSeriesCondition, we should consider implementing it directly there.
GiovanniCanali
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GiovanniCanali
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GiovanniCanali
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I know this is still a work in progress, but I have added a few comments below.
@ndem0, please remember to add the appropriate mapping to the Condition factory so that the software automatically dispatches graph time-series conditions and standard time-series conditions to the correct classes.
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| return _DataManager(input=graph) | ||
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| def evaluate(self, batch, solver): |
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This method appears to be identical to the one defined in TimeSeriesCondition and should therefore be inherited without modification.
| return torch.stack(residuals).as_subclass(torch.Tensor) | ||
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| @property | ||
| def input(self): |
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This method appears to be identical to the one defined in TimeSeriesCondition and should therefore be inherited without modification.
| residuals = [] | ||
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| # Iterate over the time steps | ||
| for step in range(1, batch["input"].shape[2]): |
There was a problem hiding this comment.
This is definitely a condition-level concern, since gradient computation must be enabled or disabled when evaluating the residual between the model prediction and the target. As you noted, the implementation should be straightforward. Since the forward method is inherited from TimeSeriesCondition, we should consider implementing it directly there.
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Added the graph time series condition.
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